Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr.

ABSTRACT:

Motivation

Genome-wide datasets produced for association studies have dramatically increased in size over the past few years, with modern datasets commonly including millions of variants measured in dozens of thousands of individuals. This increase in data size is a major challenge severely slowing down genomic analyses, leading to some software becoming obsolete and researchers having limited access to diverse analysis tools.

Results

Here we present two R packages, bigstatsr and bigsnpr, allowing for the analysis of large scale genomic data to be performed within R. To address large data size, the packages use memory-mapping for accessing data matrices stored on disk instead of in RAM. To perform data pre-processing and data analysis, the packages integrate most of the tool

SUBMITTER: Prive F 

PROVIDER: S-EPMC6084588 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature